This book is a comprehensive, hands-on guide to the basics of data mining and machine learning with a special emphasis on supervised and unsupervised learning methods. The book lays stress on the new ways of thinking needed to master in machine learning based on the Python, R, and Java programming platforms. This book first provides an understanding of data mining, machine learning and their applications, giving special attention to classification and clustering techniques. The authors offer a discussion on data mining and machine learning techniques with case studies and examples. The book also describes the hands-on coding examples of some well-known supervised and unsupervised learning techniques using three different and popular coding platforms: R, Python, and Java. This book explains some of the most popular classification techniques (K-NN, Naïve Bayes, Decision tree, Random forest, Support vector machine etc,) along with the basic description of artificial neural network and deep neural network. The book is useful for professionals, students studying data mining and machine learning, and researchers in supervised and unsupervised learning techniques.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Sanjay Chakraborty is currently an Assistant Professor of the Department of Computer Science and Engineering, JIS University, Kolkata, India. He did his B-Tech from West Bengal University of Technology, India on Information Technology in the year 2009. He completed his Master of Technology (M-Tech) from National Institute of Technology, Raipur, India in the year of 2011. He has submitted his Ph.D. thesis at AKCSIT, University of Calcutta in 2020. Mr. Chakraborty is the recipient of the University Silver Medal from NIT Raipur in 2011 for ranking first-class second in M-Tech. He has 10+ years of teaching and research experience. He has published over 50 research papers in various international journals, conferences, and book chapters. He is the author of one book on ML-based Brain-computer interfacing published by Lap Lambert, Germany. Mr. Chakraborty attended many national and international conferences in India and abroad. His research interests include Data Mining & Machine Learning and Quantum Computing. He is a professional member of IAENG and UACEE. Mr. Chakraborty is an active member of the board of reviewers in various International Journals and Conferences. He is the recipient of "INNOVATION AWARD" for outstanding achievement in the field of Innovation by Techno India Institution's Innovation Council 2019. He is also the recipient of "IEEE Young Professional Best Paper Award" in 2017. He has also achieved the top five best paper recognition by Ain Shams Engineering Journal, Elsevier. He is a reviewer of various IEEE transactions, Nature, and other reputed journals and conferences.
SK Hafizul Islam received the M.Sc. degree in Applied Mathematics from Vidyasagar University, Midnapore, India, in 2006, and the M.Tech. degree in Computer Application and the Ph.D. degree in Computer Science and Engineering in 2009 and 2013, respectively, from the Indian Institute of Technology [IIT (ISM)] Dhanbad, Jharkhand, India, under the INSPIREFellowship Ph.D. Program (funded by Department of Science and Technology, Government of India). He is currently an Assistant Professor with the Department of Computer Science and Engineering, Indian Institute of Information Technology Kalyani (IIIT Kalyani), West Bengal, India. Before joining the IIIT Kalyani, he was an Assistant Professor with the Department of Computer Science and Information Systems, Birla Institute of Technology and Science, Pilani (BITS Pilani), Rajasthan, India. He has more than eight years of teaching and ten years of research experiences. He has authored or co-authored hundred research papers in journals and conference proceedings of international reputes. His research interests include cryptography, information security, WSNs, IoT, and cloud computing. Dr. Islam is an Associate Editor for Wiley's "International Journal of Communication Systems" and "Security and Privacy" and IEEE's "IEEE Access". He was a reviewer in many reputed international journals and conferences. He was the recipient of the University Gold Medal, the S. D. Singha Memorial Endowment Gold Medal, and the Sabitri Parya Memorial Endowment Gold Medal from Vidyasagar University, in 2006. He was also the recipient of the University Gold Medal from IIT(ISM) Dhanbad in 2009 and the OPERA award from BITS Pilani in 2015. He is a senior member of the IEEE and a member of the ACM.
Dr. Debabrata Samanta is presently working as Assistant Professor, Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India. He obtained his Bachelors in Physics (Honors), from Calcutta University; Kolkata, India. He obtained his MCA, from the Academy of Technology, under WBUT, West Bengal. He obtained his PhD in Computer Science and Engg. from National Institute of Technology, Durgapur, India, in the area of SAR Image Processing. He is keenly interested in Interdisciplinary Research & Development and has experience spanning fields of SAR Image Analysis, Video surveillance, Heuristic algorithm for Image Classification, Deep Learning Framework for Detection and Classification, Blockchain, Statistical Modelling, Wireless Adhoc Network, Natural Language Processing, V2I Communication. He has successfully completed six Consultancy Projects. He has received funding under International Travel Support Scheme in 2019 for attending conference in Thailand. He has received Travel Grant for speaker in Conference, Seminar etc for two years from July, 2019. He is the owner of 20 Patents (3 Design Indian Patent and 2 Australian patent Granted, 15 Indian Patent published) and 2 copyright. He has authored and coauthored over 166 research papers in international journal (SCI/SCIE/ESCI/Scopus) and conferences including IEEE, Springer and Elsevier Conference proceeding. He has received "Scholastic Award" at 2nd International conference on Computer Science and IT application, CSIT-2011, Delhi, India. He is a co-author of 11 books and the co-editor of 7 books, available for sale on Amazon and Flipkart. He has presented various papers at International conferences and received Best Paper awards. He has author and co-authored of 20 Book Chapters. He also serves as acquisition editor for Springer, Wiley, CRC, Scrivener Publishing LLC, Beverly, USA. and Elsevier. He is a Professional IEEE Member, an Associate Life Member of Computer Society Of India (CSI) and a Life Member of Indian Society for Technical Education (ISTE). He is a Convener, Keynote speaker, Session chair, Co-chair, Publicity chair, Publication chair, Advisory Board, Technical Program Committee members in many prestigious International and National conferences. He was invited speaker at several Institutions.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book is a comprehensive, hands-on guide to the basics of data mining and machine learning with a special emphasis on supervised and unsupervised learning methods. The book lays stress on the new ways of thinking needed to master in machine learning based on the Python, R, and Java programming platforms. This book first provides an understanding of data mining, machine learning and their applications, giving special attention to classification and clustering techniques. The authors offer a discussion on data mining and machine learning techniques with case studies and examples. The book also describes the hands-on coding examples of some well-known supervised and unsupervised learning techniques using three different and popular coding platforms: R, Python, and Java. This book explains some of the most popular classification techniques (K-NN, Naïve Bayes, Decision tree, Random forest, Support vector machine etc,) along with the basic description of artificial neural network and deep neural network. The book is useful for professionals, students studying data mining and machine learning, and researchers in supervised and unsupervised learning techniques. 220 pp. Englisch. N° de réf. du vendeur 9783030930905
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book is a comprehensive, hands-on guide to the basics of data mining and machine learning with a special emphasis on supervised and unsupervised learning methods. The book lays stress on the new ways of thinking needed to master in machine learning based on the Python, R, and Java programming platforms. This book first provides an understanding of data mining, machine learning and their applications, giving special attention to classification and clustering techniques. The authors offer a discussion on data mining and machine learning techniques with case studies and examples. The book also describes the hands-on coding examples of some well-known supervised and unsupervised learning techniques using three different and popular coding platforms: R, Python, and Java. This book explains some of the most popular classification techniques (K-NN, Naïve Bayes, Decision tree, Random forest, Support vector machine etc,) along with the basic description of artificial neural network and deep neural network. The book is useful for professionals, students studying data mining and machine learning, and researchers in supervised and unsupervised learning techniques.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 220 pp. Englisch. N° de réf. du vendeur 9783030930905
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Taschenbuch. Etat : Neu. Data Classification and Incremental Clustering in Data Mining and Machine Learning | Sanjay Chakraborty (u. a.) | Taschenbuch | xxi | Englisch | 2023 | Springer | EAN 9783030930905 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. N° de réf. du vendeur 126842667
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is a comprehensive, hands-on guide to the basics of data mining and machine learning with a special emphasis on supervised and unsupervised learning methods. The book lays stress on the new ways of thinking needed to master in machine learning based on the Python, R, and Java programming platforms. This book first provides an understanding of data mining, machine learning and their applications, giving special attention to classification and clustering techniques. The authors offer a discussion on data mining and machine learning techniques with case studies and examples. The book also describes the hands-on coding examples of some well-known supervised and unsupervised learning techniques using three different and popular coding platforms: R, Python, and Java. This book explains some of the most popular classification techniques (K-NN, Naïve Bayes, Decision tree, Random forest, Support vector machine etc,) along with the basic description of artificial neural network and deep neural network. The book is useful for professionals, students studying data mining and machine learning, and researchers in supervised and unsupervised learning techniques. N° de réf. du vendeur 9783030930905
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